About the Role

We're building AI products that solve real problems for real customers. This role sits at the intersection of product and engineering– you'll own features end-to-end, from understanding user problems to shipping production code that scales.

Applied AI product engineering is a new discipline. You won't just be integrating APIs – you'll be designing AI systems that work reliably in production, building evaluation frameworks to measure quality, and iterating rapidly based on real user feedback. You'll work directly with customers to understand their workflows and translate that understanding into product decisions.

This is not a research role. We're looking for engineers who ship. You'll be measured by the products you deliver and the problems you solve, not by papers published or models trained. The best candidates combine deep technical skills with strong product intuition and a relentless focus on user outcomes.

What You'll Do

Design, build, and ship AI-powered product features from concept through production deployment

Develop and maintain LLM-based systems including RAG pipelines, agents, and workflow automation

Build evaluation frameworks and monitoring systems to ensure AI quality and reliability

Work directly with customers to understand problems, gather feedback, and validate solutions

Collaborate with product and design to define roadmap and prioritize features based on impact

Optimize system performance, cost, and latency as usage scales

Contribute to technical architecture decisions and establish engineering best practices

Qualifications

4+ years of software engineering experience, with at least 1-2 years building AI/ML-powered products

Strong proficiency in Python; experience with TypeScript/JavaScript for full-stack development

Hands-on experience with LLMs in production: prompt engineering, RAG systems, fine-tuning, or agent frameworks

Solid understanding of ML fundamentals: embeddings, vector databases, evaluation metrics, and model selection

Experience building and maintaining production systems with high reliability requirements

Strong product intuition, ability to translate ambiguous user needs into concrete technical solutions

Excellent communication skills and comfort working directly with customers and stakeholders

BS/MS in Computer Science, or equivalent practical experience

Nice to Have

Experience with AI infrastructure: LangChain, LlamaIndex, vector databases (Pinecone, Weaviate, Chroma)

Background in NLP, information retrieval, or search systems

Previous startup experience, especially as an early engineer or technical co-founder

Domain expertise in financial services, legal, healthcare, or other enterprise SaaS verticals

Contributions to open-source AI/ML projects

Experience building developer tools or platforms